June 8, 2026

Artificial intelligence in health and social care: CQC's role, expectations and plans

The use of artificial intelligence (AI) continues to increase across health and social care. As England’s independent regulator of health and social care, we encourage the use of innovative technologies, including AI, where the technology benefits people and results in more effective and efficient services. 

AI presents enormous opportunities, though not without risks. We have outlined some of the benefits and risks of AI and set out how CQC’s regulatory work has a role in ensuring AI contributes to safe, equitable and person-centred care. The principles of good use of AI provide a high-level illustration of what this means for providers of health and social care services.


AI in health and social care


The use of AI continues to grow quickly. In health and social care, AI is now:


  • answering questions through chatbots and generative AI
  • identifying problems in X-rays and scans, supporting diagnosis and treatment planning
  • writing up notes and consultations, for example in GP and outpatient settings
  • supporting administrative tasks
  • predicting hospital admissions
  • planning how to make better use of resources
  • monitoring people who are in more vulnerable circumstances, through wearable devices and home sensors, for example to identify people at risk of falls.

AI and AI-driven innovation remain central to government’s vision for more effective public services, including health and social care. CQC and regulators across all sectors have a role in encouraging the use of AI through innovation-friendly regulation as discussed in the AI Opportunities Action Plan (January 2025).


Potential benefits and risks of AI


Benefits


In health and social care, we are beginning to see promising use of AI. For example, this results in:


  • faster diagnosis from medical images
  • enhanced clinical efficiency and workflow
  • earlier identification of patients who are higher risk
  • better resource management
  • improved monitoring for people who are more vulnerable.

We now need to better understand how these examples benefit people using services through high-quality care that is equitable in terms of access and outcomes.


Risks


Alongside potential benefits, AI comes with risks. For example:

  • it can result in more health inequalities in terms of access and poorer outcomes
  • it can make mistakes, and lead to misdiagnoses, which can be difficult to spot, sometimes only after people experience harm when using a service
  • it can de-personalise health and social care
  • people may not understand AI and therefore refuse care without having clear and accessible information to explain it
  • if things go wrong, accountability and liability can be unclear
  • staff may lack trust, confidence and training to use AI, to check outputs, or to understand whether AI improves outcomes for people using services
  • those using AI might become de-skilled
  • AI and the need for human oversight can increase workload
  • it can hallucinate and present untrue information, authoritatively as fact
  • when used inappropriately, for example when applying for CQC registration, AI can lead to wrong decisions
  • it can pose risks to privacy, data protection and confidentiality
  • it has a significant and growing carbon footprint, which can undermine environmental sustainability goals, as use of land and water by data centres can make inequalities worse.

Different AI technologies pose different risks that vary depending on where or in what setting they are used. Risks in some settings may be harder to spot and quantify.


CQC’s role in the regulation and safe use of AI


Our vision is for everyone to receive safe, effective and compassionate care. CQC regulates health and adult social care in England, we work with the public, systems and providers of care to protect people, and to promote and improve quality of care, including AI-enabled care. We do not assess or approve specific technologies but have a role in ensuring that technology including AI contributes to safe, effective and equitable care across all settings and services.

Most regulations that we enforce have a role in making sure that innovative technologies including AI improve the quality of care and the outcomes for people using services. For example:


  • Regulation 9: Person-centred care (giving people the right information to make choices)
  • Regulation 10: Dignity and respect (protecting privacy and treating everyone fairly)
  • Regulation 11: Consent (making sure staff who obtain consent have the necessary knowledge of the care and/or treatment they are asking people to consent to)
  • Regulation 12: Safe care and treatment (ensuring equipment, for example AI is safe)
  • Regulation 17: Good governance (adhering to regulation, effective risk management systems, and monitoring outputs).

What does this mean for providers?


We encourage innovation and technology, including AI, where it benefits people and where the innovation supports high-quality, equitable health and social care. Using AI to provide health and social care in line with the regulations means providers must follow the following principles:


  • AI to support, not to replace: AI can enhance, but not replace human decision making.
  • Human oversight: AI outputs and processes are continuously monitored and evaluated.
  • Transparency and choice: People who use services have appropriate information to make informed decisions about their care, including the role of AI in care pathways. Non-digital routes to care are offered if needed, also considering digital skills and connectivity.
  • Safety and reliability: Providers ensure that introducing and using AI provides safe care and equitable outcomes for people.
  • Security: The technology is resilient to cyber-attacks and sensitive information is stored and processed securely to comply with the General Data Protection Regulation.
  • Fairness and impartiality: Good AI accelerates equity of care in terms of access and outcomes. For example, it provides accurate results across geographies and population groups and any potential known biases are mitigated.
  • AI readiness and training: Those using AI are sufficiently trained and confident in using the technology, and they assess whether it can be integrated into existing pathways.
  • Effective governance: There are effective mechanisms such as risk assessments to ensure AI contributes to high-quality, equitable care, and established systems to recognise, report and investigate when something goes wrong so that lessons are learned and solutions implemented.
  • Data Protection Impact Assessment (DPIA): A DPIA assesses and documents risks to privacy and data subject rights to understand and minimise any interference with people’s rights, to enable lawful use of AI.
  • Accountability: There are clear mechanisms for addressing issues or harm caused by AI.
  • Procurement: AI tools are procured in line with relevant regulatory standards.

We have aligned these principles with those published by other organisations such as the British Medical Association (BMA, Principles for AI and its application in healthcare, 2024) and the World Health Organisation (WHO, Ethics and governance of artificial intelligence for health, 2024) and linked back to the regulations we enforce.


Next steps


CQC is currently working to develop and implement an updated regulatory model including new assessment frameworks, supported by operational processes and digital systems.


Following our consultation Better regulation, better care, we published new draft sector-specific assessment frameworks in March 2026 for further engagement and consultation. We have included references in those draft frameworks where appropriate to encouraging innovative use of technology, including artificial intelligence, as part of ensuring people have timely access to care, treatment and support.


As we develop and roll out our updated assessment frameworks, we will continue to explore the implications of providers’ use of AI for how we regulate, for example, how we register, assess, rate and encourage improvement. This includes the following 3 interlinked areas of work throughout 2026/27 and beyond:


1. Reflecting providers’ use of AI in our regulatory activities

Alongside work on our new assessment frameworks, we are considering what the use of AI in health and social care means for how we regulate, for example for how we:


  • Register: our role is to ensure providers meet the fundamental standards of care and other regulations when delivering regulated activities, regardless of technology. Where providers use technology, including AI, we need to understand the impact on care provision so that we can support improvement by sharing examples of good, innovative care.
  • Assess: these activities focus on whether providers meet fundamental standards and other relevant regulations regardless of technology. Where providers use AI, we must know whether AI facilitates high-quality, equitable care. We are considering any implications on how we apply our new assessment frameworks and what additional guidance might be needed.
  • Rate: the absence or presence of AI does not predict a specific rating.
  • Enforce: this includes how we respond if AI causes risks to safety or access to care.
  • Encourage improvement: we need to be able to recognise when AI contributes to outstanding care to share examples of good and innovative practice.

2. Further guidance


Our new assessment frameworks will be rolled out alongside supporting guidance for providers. As technology including AI evolves, we will keep requirements for AI-specific guidance and training under review. We may develop AI guidance tailored to providers across different sectors and settings alongside building internal capability.


3. Continued engagement


Continued engagement will help ensure our position and guidance relating to AI remain up to date. We will also continue work with:


  • Other regulators: ens
  • during data and digital technologies, including AI, contribute to safe and high-quality health and social care is also relevant to the remits of different regulators and bodies. The AI and Digital Regulations Service provides further information, including about the role of the Medicines & Healthcare products Regulatory Agency (MHRA), the UK’s regulator of medicines and medical devices, including software and AI as a medical device. The MHRA has established the National Commission into the Regulation of AI to review current regulations and to provide recommendations for a regulatory framework for AI in healthcare. We are working with the commission and will use its outputs in our work. We will continue working with other regulators and bodies to ensure clear regulatory remits, identify and respond to gaps and develop mechanisms to monitor AI-readiness across health and social care.
  • Industry and providers: clear regulatory requirements are crucial for ensuring data and digital technologies contribute to safe and high-quality care. Therefore, we will continue and expand collaborative work with industry and AI developers and providers of health and social care. This will support us in providing up-to-date and clear guidance.
  • Academic and not for profit organisations: this work will facilitate AI readiness at provider and system level through tools and guidance that is based on the best available evidence, and by using our unique oversight position of health and social care.

https://www.cqc.org.uk/about-us/transparency/artificial-intelligence-health-social-care-cqcs-role-expectations-plans


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Providers take the strain through thinner margins and deferred investment, and families often meet it through the higher fees paid by those who fund their own care, on average 41 per cent more than the council-funded rate. One settlement, built as a system The CAA argues that these are symptoms of a single structural mismatch, and that they need to be fixed together. Its proposed national funding settlement rests on three principles: pooling the financial risk of demographic change nationally, a statutory entitlement to support triggered by assessed need, and continued local delivery within a national framework. In practice, the settlement has five main components: A ring-fenced national care grant , distributed to councils on a needs-adjusted formula, so that funding follows need rather than local fiscal capacity. A reformed means test , with a raised capital threshold, frozen at £23,250 since 2010/11, and a lifetime cap on what any individual can be asked to pay. 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